• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.171-182
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• 2015

We propose a camera system to acquire indoor stereo omni-directional images and its calibration method. These images can be utilized for indoor precise mapping and sophisticated imagebased services. The proposed system is configured with a rotating stereo line camera system, providing stereo omni-directional images appropriate to stable stereoscopy and precise derivation of object point coordinates. Based on the projection model, we derive a mathematical model for the system calibration. After performing the system calibration, we can estimate object points with an accuracy of less than ${\pm}16cm$ in indoor space. The proposed system and calibration method will be applied to indoor precise 3D modeling.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.188-195
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• 2024

This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a neural network-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such as hazing and low contrast occur, it is hard to apply conventional simultaneous localization and mapping (SLAM) methods. At the same time, the behavior of Autonomous Underwater Vehicle (AUV) is computationally constrained. In this paper, we utilize a neural network-based image enhancement method to improve pose estimation and mapping quality and apply a sliding window-based mesh expansion method to enable lightweight, fast, and photorealistic mapping. To validate our results, we utilize real-world and indoor synthetic datasets. We performed qualitative validation with the real-world dataset and quantitative validation by modeling images from the indoor synthetic dataset as underwater scenes.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.487-492
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• 2009

A large-scaled research project titled "Intelligent Excavating System (IES)" sponsored by Korean government has launched in 2006. An issue of real-time 3D terrain modeling has become a crucial point for successful implementation of IES due to many application limitations of state-of-the-art techniques developed in various high-technology fields. Many feasible technologies such as laser scanning, structured lighting and so on were widely reviewed by professionals and researchers for one year. Various efforts such as literature reviews, interviews, and indoor experiments make us select a structural light technique and stereo vision technique as appropriate techniques for accomplishment of real-time 3D terrain modeling. It, however, revealed that off-the-shelf products of structural light and stereo-vision technique had many technical problems which should be resolved for practical applications in IES. This study introduces diverse methods modifying off-the-shelf package of the structural light method, one of feasible techniques and eventually allowing this technique to be successfully utilized for achieving fundamental research goals. This study also presents many efforts to resolve practical difficulties of this technique considering basic characteristics of excavating operations and particular environment of construction sites. Findings showed in this study would be beneficial for other researchers to conduct new researches for application of vision techniques to construction fields by provision of detail issues about practical application and diverse practical methods as solutions overcoming these issues.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.66-75
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• 2010

In Augmented Reality, it needs restoration and tracking of a real-time scene structure for the augmented 3D model from input video or images. Most of the previous approaches construct accurate 3D models in advance and try to fit them in real-time. However, it is difficult to measure 3D model accurately and requires long pre-processing time to construct exact 3D model specifically. In this research, we suggest a real-time scene structure analysis method for the wide indoor mobile augmented reality, using only generic models without exact pre-constructed models. Our approach reduces cost and time by removing exact modeling process and demonstrates the method for restoration and tracking of the indoor repetitive scene structure such as corridors and stairways in different scales and details.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.33-41
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• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• Spatial Information Research
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• v.23 no.4
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• pp.91-101
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• 2015

Due to recent increase of indoor spatial information demands, several international standards have been published for indoor spatial information. OGC has also recently published two standards for indoor space; CityGML and IndoorGM. CityGML aims to provide a standard for 3D city modeling and the level of details (LoD) 4 covers the indoor space. IndoorGML focuses only on indoor space and provides several functions to complement the weakness of CityGML. It is therefore recommended to apply IndoorGML as a combination with CityGML. However since the weakness and strengths between these standards are not yet fully studied and understood, there is no well-defined guideline to apply them in a proper way. It means that we need to carry out a comparative study between them for their proper integration. For this reason, we discuss the pros and cons of these standards from two use-cases. The sites for the use-cases cover Lotte World Mall and Jongno-5 subway station, respectively. We studied these use-cases to compare CityGML and IndoorGML through the data construction of CityGML and IndoorGML for these sites. And based on several application scenarios, we also analyzed the weakness and strengths of each standard from different viewpoints. We expect that these comparative studies will be helpful to make a guideline on the application and integration between CityGML and CityGML.

• Journal of the Korean Geosynthetics Society
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• v.15 no.4
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• pp.33-42
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• 2016

Discrete Element Method was conducted for rock and coarse-grained materials in development of granular mechanics and related numerical model due to analyze and apply micromechanical property. And it was verified that the analysis to consider bonding effect was insufficient. In this study, to overcome limits of existing method, it was conducted to analyze difference between indoor test result and bonding effect using $PFC^{3D)}$. For indoor test of mixed soil, uniaxial compression tests by curing time and by cement content were performed. And, DEM to suitable for each condition of indoor test was conducted. In the result of this study, in terms of geotechnics, it was verified that DEM can be used for application as numerical laboratory as well as prediction of micro and macro behavior about bonding effect of mixed soil.

• Journal of KIISE
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• v.44 no.3
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• pp.332-337
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• 2017

When using IFC data consisting of STEP schema based on the EXPRESS language, it is not easy for collaborating project stakeholders to share BIM modeling shape information. The IFC viewer application must be installed on the desktop PC to review the BIM modeling shape information defined within the IFC, because the IFC viewer application not only parse STEP structure information model but also process the 3D feature construction for a 3D visualization. Therefore, we propose a lightweight data structure design for web visualization by parsing IFC data and constructing 3D modeling data. Our experimental results show the weight reduction of IFC data is about 40% of original file size and the web visualization is able to see the same quality with all web browsers which support WebGL on PCs and smartphones. If applied research is conducted about the web visualization based on IFC data of the last construction phase, it could be utilized in various fields ranging from the facility maintenance to indoor location-based services.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.211-221
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• 2012

To utilize omni-directional images acquired by a rotating line camera for indoor spatial information services, we should register precisely the images with respect to an indoor coordinate system. In this study, we thus develop a georeferencing method to estimate the exterior orientation parameters of an omni-directional image - the position and attitude of the camera at the acquisition time. First, we derive the collinearity equations for the omni-directional image by geometrically modeling the rotating line camera. We then estimate the exterior orientation parameters using the collinearity equations with indoor control points. The experimental results from the application to real data indicate that the exterior orientation parameters is estimated with the precision of 1.4 mm and $0.05^{\circ}$ for the position and attitude, respectively. The residuals are within 3 and 10 pixels in horizontal and vertical directions, respectively. Particularly, the residuals in the vertical direction retain systematic errors mainly due to the lens distortion, which should be eliminated through a camera calibration process. Using omni-directional images georeferenced precisely with the proposed method, we can generate high resolution indoor 3D models and sophisticated augmented reality services based on the models.